A tool to improve functional outcome assessment of a multimodal program for patients with chronic low back pain: A study on walk tests (at comfortable and fast speed)
Bibliographic record
Abstract
BACKGROUND: Tools for functional assessment of chronic low back pain (LBP) are lacking. OBJECTIVE: To determine the correlations and the responsiveness of the 400 m comfortable walk test (400 mCWT) and the 200 m fast-walk test (200 mFWT) in the functional assessment of a multimodal program. METHODS: One hundred and twenty-seven participants (68 females) with LBP and with or without radicular pain completed a Quebec Back Pain Disability Scale, a Sorensen test, a Shirado test, a 400 mCWT and a 200 mFWT, at baseline and at the end of the program. RESULTS: No significant side effect was reported during walk tests. Walking speed was significantly increased after the program (0.18 ± 0.15 m.s-1 for the 400 mCWT and 0.17 ± 0.17 m.s-1 for the 200 mFWT). Clinical parameters were also significantly improved (82.02 ± 83.1 seconds for the Shirado, 92.1 ± 100.1 seconds for the Sorensen, -14.0 ± 12.9 for the Quebec scale). A significant relationship was found between the increase in walking speed for the two walk tests and the improvement of the Quebec scale. The gait speed improvement was close to the minimal clinically important change (95% confidence interval: 0.14-0.22) determined from the Quebec scale threshold (minimum detectable change). CONCLUSIONS: Both 400 mCWT and 200 mFWT are correlated with functional parameters and are responsive for the functional assessment of LBP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".